Best Papers
CSC 262 - Computer Vision - Weinman
1 Introduction
We will read and discuss in class one or two of the best papers from
the most recent top systems conferences. In this way, we'll be learning
together:
- How to read research papers
- About the latest in computer vision research
- What the community thinks is currently important
2 Candidates
Our candidates (listed in no particular order) are drawn from CVPR
2013, CVPR 2014, ECCV 2014, and ICCV 2013. See the list of papers
below and read their abstracts.
- Fast,
Accurate Detection of 100,000 Object Classes on a Single Machine
Thomas Dean, Jay Yagnik, Mark Ruzon, Mark Segal, Jonathon Shlens,
and Sudheendra Vijayanarasimhan. (CVPR '13)
- Discriminative
Non-blind Deblurring. Uwe Schmidt, Carsten Rother, Sebastian Nowozin,
Jeremy Jancsary, and Stefan Roth. (CVPR '13)
- What
Camera Motion Reveals About Shape with Unknown BRDF. Manmohan Chandraker.
(CVPR '14)
- Partial
Optimality by Pruning for MAP-inference with General Graphical Models.
Paul Swoboda, Bogdan Savchynskyy, Joerg Kappes, Christoph Schnörr
(CVPR '14)
- From
Large Scale Image Categorization to Entry- Level Categories. Vicente
Ordonez, Jia Deng, Yejin Choi, Alexander Berg and Tamara Berg. (ICCV
'13)
- Scene
Chronology. Kevin Matzen and Noah Snavely. (ECCV '14)
- Large-Scale
Object Classification using Label Relation Graphs. Jia Deng, Nan
Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan
Li, Hartmut Neven, Hartwig Adam. (ECCV '14)
3 Voting
Please vote by emailing your TOP TWO choices (by number) to the instructor
by Friday May 1.
4 Responses
You will be required to submit a brief 225-275 word critical response
to the paper before class to help prepare you for the discussion.
In particular, you should note:
- What problem are they trying to solve?
- Why is the problem important?
- How does it currently get done and what are the limitations?
- What are the authors' goals?
- Does the paper have a scientific thesis? Is it falsifiable?
- What are the paper's claims?
- Are the claims substantiated (by theory or experiment)? If so, how?
- What are the limitations of the proposed approach?
- Are there ways to extend the method?
You should include at least two primary points that critique, dispute,
extend, or reinforce the paper. Submit your responses (in PDF format
only) via P-Web; they are due at the beginnning of class on the day
of discussion.
Acknowledgments
The questions above are inspired by and adapted from the following
works.
Fong, Philip W.L., Reading a computer science research
paper, SIGCSE Bulletin 41, 2 (2009), pp. 138-140.
doi:10.1145/1595453.1595493
Keshav, S., How to read a paper, SIGCOMM
Computer Communication Review 37, 3 (2007), pp. 83-84. doi:dx.doi.org/10.1145/1273445.1273458
Jerod Weinman
Created 20 June 2008
Revised 1 December 2008
Revised 17 August 2012
Revised 7 August 2014
Revised 13 January 2015